Field of the Invention
Embodiments of the present invention relate generally to network analysis and, more specifically, to a node-centric analysis of dynamic networks.
Description of the Related Art
A network generally includes a collection of nodes that are interconnected with one another via a set of links. For example, a computer network could include a collection of computers interconnected with one another via a set of wired or wireless data connections. Alternatively, a power distribution network could include a collection of power substations interconnected with one another via a set of power lines. Various tools exist for analyzing and visualizing the topologies of networks at given points in time. For example, a conventional network analysis tool could analyze a network and then generate a visualization that depicts the nodes of the network as well as the various interconnections between those nodes, at a particular point in time.
Network analysis tools are generally used to optimize the overall operation of the network. For example, a network analysis tool could be used to generate a visualization of the computer network mentioned above. Based on that visualization, a network engineer could determine that the interconnections between the network nodes should be adjusted in order to more effectively load balance network communications. By making those adjustments, the overall network throughput and/or quality of service can be increased.
One drawback associated with conventional network analysis tools is that those tools only generate visualizations of networks at individual points in time. The typical visualizations generated therefore fail to capture time-varying network dynamics. This shortcoming is especially problematic when analyzing networks that can change rapidly over short durations of time. For example, returning to the computer network example discussed above, if the computers in the network were able to dynamically change their respective connections, then analyzing the interconnections between those computers at a particular point in time would not yield any useful insight about the network because the network connections could be completely different only a short time later.
As the foregoing illustrates, what is needed in the art are more effective approaches to analyzing and visualizing networks.